NeuroBus - Architecture for an Ultra-Flexible Neural Interface.

This article presents the system architecture for an implant concept called NeuroBus. Tiny distributed direct digitizing neural recorder ASICs on an ultra-flexible polyimide substrate are connected in a bus-like structure, allowing short connections between electrode and recording front-end with low wiring effort and high customizability. The small size (344 µm × 294 µm) of the ASICs and the ultraflexible substrate allow a low bending stiffness, enabling the implant to adapt to the curvature of the brain and achieving high structural biocompatibility. We introduce the architecture, the integrated building blocks, and the post-CMOS processes required to realize a NeuroBus, and we characterize the prototyped direct digitizing neural recorder front-end as well as polyimide-based ECoG brain interface. A rodent animal model is further used to validate the joint capability of the recording front-end and thin-film electrode array.

Resolving the prefrontal mechanisms of adaptive cognitive behaviors: A cross-species perspective.

The prefrontal cortex (PFC) enables a staggering variety of complex behaviors, such as planning actions, solving problems, and adapting to new situations according to external information and internal states. These higher-order abilities, collectively defined as adaptive cognitive behavior, require cellular ensembles that coordinate the tradeoff between the stability and flexibility of neural representations. While the mechanisms underlying the function of cellular ensembles are still unclear, recent experimental and theoretical studies suggest that temporal coordination dynamically binds prefrontal neurons into functional ensembles. A so far largely separate stream of research has investigated the prefrontal efferent and afferent connectivity. These two research streams have recently converged on the hypothesis that prefrontal connectivity patterns influence ensemble formation and the function of neurons within ensembles. Here, we propose a unitary concept that, leveraging a cross-species definition of prefrontal regions, explains how prefrontal ensembles adaptively regulate and efficiently coordinate multiple processes in distinct cognitive behaviors.

FreiBox: A Versatile Open-Source Behavioral Setup for Investigating the Neuronal Correlates of Behavioral Flexibility via 1-Photon Imaging in Freely Moving Mice.

To survive in a complex and changing environment, animals must adapt their behavior. This ability is called behavioral flexibility and is classically evaluated by a reversal learning paradigm. During such a paradigm, the animals adapt their behavior according to a change of the reward contingencies. To study these complex cognitive functions (from outcome evaluation to motor adaptation), we developed a versatile, low-cost, open-source platform, allowing us to investigate the neuronal correlates of behavioral flexibility with 1-photon calcium imaging. This platform consists of FreiBox, a novel low-cost Arduino behavioral setup, as well as further open-source tools, which we developed and integrated into our framework. FreiBox is controlled by a custom Python interface and integrates a new licking sensor (strain gauge lickometer) for controlling spatial licking behavioral tasks. In addition to allowing both discriminative and serial reversal learning, the Arduino can track mouse licking behavior in real time to control task events in a submillisecond timescale. To complete our setup, we also developed and validated an affordable commutator, which is crucial for recording calcium imaging with the Miniscope V4 in freely moving mice. Further, we demonstrated that FreiBox can be associated with 1-photon imaging and other open-source initiatives (e.g., Open Ephys) to form a versatile platform for exploring the neuronal substrates of licking-based behavioral flexibility in mice. The combination of the FreiBox behavioral setup and our low-cost commutator represents a highly competitive and complementary addition to the recently emerging battery of open-source initiatives.

Conserved structures of neural activity in sensorimotor cortex of freely moving rats allow cross-subject decoding.

Our knowledge about neuronal activity in the sensorimotor cortex relies primarily on stereotyped movements that are strictly controlled in experimental settings. It remains unclear how results can be carried over to less constrained behavior like that of freely moving subjects. Toward this goal, we developed a self-paced behavioral paradigm that encouraged rats to engage in different movement types. We employed bilateral electrophysiological recordings across the entire sensorimotor cortex and simultaneous paw tracking. These techniques revealed behavioral coupling of neurons with lateralization and an anterior-posterior gradient from the premotor to the primary sensory cortex. The structure of population activity patterns was conserved across animals despite the severe under-sampling of the total number of neurons and variations in electrode positions across individuals. We demonstrated cross-subject and cross-session generalization in a decoding task through alignments of low-dimensional neural manifolds, providing evidence of a conserved neuronal code.

3D pose estimation enables virtual head fixation in freely moving rats.

The impact of spontaneous movements on neuronal activity has created the need to quantify behavior. We present a versatile framework to directly capture the 3D motion of freely definable body points in a marker-free manner with high precision and reliability. Combining the tracking with neural recordings revealed multiplexing of information in the motor cortex neurons of freely moving rats. By integrating multiple behavioral variables into a model of the neural response, we derived a virtual head fixation for which the influence of specific body movements was removed. This strategy enabled us to analyze the behavior of interest (e.g., front paw movements). Thus, we unveiled an unexpectedly large fraction of neurons in the motor cortex with tuning to the paw movements, which was previously masked by body posture tuning. Once established, our framework can be efficiently applied to large datasets while minimizing the experimental workload caused by animal training and manual labeling.

Multichannel optogenetics combined with laminar recordings for ultra-controlled neuronal interrogation.

Simultaneous large-scale recordings and optogenetic interventions may hold the key to deciphering the fast-paced and multifaceted dialogue between neurons that sustains brain function. Here we have taken advantage of thin, cell-sized, optical fibers for minimally invasive optogenetics and flexible implantations. We describe a simple procedure for making those fibers side-emitting with a Lambertian emission distribution. Here we combined those fibers with silicon probes to achieve high-quality recordings and ultrafast multichannel optogenetic inhibition. Furthermore, we developed a multi-channel optical commutator and general-purpose patch-cord for flexible experiments. We demonstrate that our framework allows to conduct simultaneous laminar recordings and multifiber stimulations, 3D optogenetic stimulation, connectivity inference, and behavioral quantification in freely moving animals. Our framework paves the way for large-scale photo tagging and controlled interrogation of rapid neuronal communication in any combination of brain areas.

Multifunctional optrode for opsin delivery, optical stimulation, and electrophysiological recordings in freely moving rats.

Objective. Optogenetics involves delivery of light-sensitive opsins to the target brain region, as well as introduction of optical and electrical devices to manipulate and record neural activity, respectively, from the targeted neural population. Combining these functionalities in a single implantable device is of great importance for a precise investigation of neural networks while minimizing tissue damage.Approach. We report on the development, characterization, andin vivovalidation of a multifunctional optrode that combines a silicon-based neural probe with an integrated microfluidic channel, and an optical glass fiber in a compact assembly. The silicon probe comprises an 11-µm-wide fluidic channel and 32 recording electrodes (diameter 30µm) on a tapered probe shank with a length, thickness, and maximum width of 7.5 mm, 50µm, and 150µm, respectively. The size and position of fluidic channels, electrodes, and optical fiber can be precisely tuned according to thein vivoapplication.Main results.With a total system weight of 0.97 g, our multifunctional optrode is suitable for chronicin vivoexperiments requiring simultaneous drug delivery, optical stimulation, and neural recording. We demonstrate the utility of our device in optogenetics by injecting a viral vector carrying a ChR2-construct in the prefrontal cortex and subsequent photostimulation of the transduced neurons while recording neural activity from both the target and adjacent regions in a freely moving rat for up to 9 weeks post-implantation. Additionally, we demonstrate a pharmacological application of our device by injecting GABA antagonist bicuculline in an anesthetized rat brain and simultaneously recording the electrophysiological response.Significance. Our triple-modality device enables a single-step optogenetic surgery. In comparison to conventional multi-step surgeries, our approach achieves higher spatial specificity while minimizing tissue damage.

Distinct dynamics of neuronal activity during concurrent motor planning and execution.

The smooth conduct of movements requires simultaneous motor planning and execution according to internal goals. So far it remains unknown how such movement plans are modified without interfering with ongoing movements. Previous studies have isolated planning and execution-related neuronal activity by separating behavioral planning and movement periods in time by sensory cues. Here, we separate continuous self-paced motor planning from motor execution statistically, by experimentally minimizing the repetitiveness of the movements. This approach shows that, in the rat sensorimotor cortex, neuronal motor planning processes evolve with slower dynamics than movement-related responses. Fast-evolving neuronal activity precees skilled forelimb movements and is nested within slower dynamics. We capture this effect via high-pass filtering and confirm the results with optogenetic stimulations. The various dynamics combined with adaptation-based high-pass filtering provide a simple principle for separating concurrent motor planning and execution.

Spontaneous activity competes with externally evoked responses in sensory cortex.

The interaction between spontaneous and externally evoked neuronal activity is fundamental for a functional brain. Increasing evidence suggests that bursts of high-power oscillations in the 15- to 30-Hz beta-band represent activation of internally generated events and mask perception of external cues. Yet demonstration of the effect of beta-power modulation on perception in real time is missing, and little is known about the underlying mechanism. Here, we used a closed-loop stimulus-intensity adjustment system based on online burst-occupancy analyses in rats involved in a forepaw vibrotactile detection task. We found that the masking influence of burst occupancy on perception can be counterbalanced in real time by adjusting the vibration amplitude. Offline analysis of firing rates (FRs) and local field potentials across cortical layers and frequency bands confirmed that beta-power in the somatosensory cortex anticorrelated with sensory evoked responses. Mechanistically, bursts in all bands were accompanied by transient synchronization of cell assemblies, but only beta-bursts were followed by a reduction of FR. Our closed loop approach reveals that spontaneous beta-bursts reflect a dynamic state that competes with external stimuli.

Cortical gamma-band resonance preferentially transmits coherent input.

Synchronization has been implicated in neuronal communication, but causal evidence remains indirect. We use optogenetics to generate depolarizing currents in pyramidal neurons of the cat visual cortex, emulating excitatory synaptic inputs under precise temporal control, while measuring spike output. The cortex transforms constant excitation into strong gamma-band synchronization, revealing the well-known cortical resonance. Increasing excitation with ramps increases the strength and frequency of synchronization. Slow, symmetric excitation profiles reveal hysteresis of power and frequency. White-noise input sequences enable causal analysis of network transmission, establishing that the cortical gamma-band resonance preferentially transmits coherent input components. Models composed of recurrently coupled excitatory and inhibitory units uncover a crucial role of feedback inhibition and suggest that hysteresis can arise through spike-frequency adaptation. The presented approach provides a powerful means to investigate the resonance properties of local circuits and probe how these properties transform input and shape transmission.

Prefrontal contributions to action control in rodents.

The rodent medial prefrontal cortex (mPFC) is typically considered to be involved in cognitive aspects of action control, e.g., decision making, rule learning and application, working memory and generally guiding adaptive behavior (Euston, Gruber, & McNaughton, 2012). These cognitive aspects often occur on relatively slow time scales, i.e., in the order of several trials within a block structure (Murakami, Shteingart, Loewenstein, & Mainen, 2017). In this way, the mPFC is able to set up a representational memory (Goldman-Rakic, 1987). On the other hand, the mPFC can also impact action control more directly (i.e., more on the motoric and less cognitive side). This impact on motor control manifests on faster time scales, i.e., on a single trial level (Hardung et al., 2017). While the more cognitive aspects have been reviewed previously as well as in other subchapters of this book, we explicitly focus on the latter aspect in this chapter, particularly on movement inhibition. We discuss models of prefrontal motor interactions, the impact of the behavioral paradigm, evidences for mPFC involvement in action control, and the anatomical connections between mPFC and motor cortex.

Effects of Optogenetic Stimulation of Primary Somatosensory Cortex and Its Projections to Striatum on Vibrotactile Perception in Freely Moving Rats.

Tactile sensation is one of our primary means to collect information about the nearby environment and thus crucial for daily activities and survival. Therefore, it is of high importance to restore sensory feedback after sensory loss. Optogenetic manipulation allows local or pathway-specific write-in of information. However, it remains elusive whether optogenetic stimulation can be interpreted as tactile sensation to guide operant behavior and how it is integrated with tactile stimuli. To address these questions, we employed a vibrotactile detection task combined with optogenetic neuromodulation in freely moving rats. By bidirectionally manipulating the activity of neurons in primary somatosensory cortex (S1), we demonstrated that optical activation as well as inhibition of S1 reduced the detection rate for vibrotactile stimuli. Interestingly, activation of corticostriatal terminals improved the detection of tactile stimuli, while inhibition of corticostriatal terminals did not affect the performance. To manipulate the corticostriatal pathway more specifically, we employed a dual viral system. Activation of corticostriatal cell bodies disturbed the tactile perception while activation of corticostriatal terminals slightly facilitated the detection of vibrotactile stimuli. In the absence of tactile stimuli, both corticostriatal cell bodies as well as terminals caused a reaction. Taken together, our data confirmed the possibility to restore sensation using optogenetics and demonstrated that S1 and its descending projections to striatum play differential roles in the neural processing underlying vibrotactile detection.

Functional interrogation of neural circuits with virally transmitted optogenetic tools.

The vertebrate brain comprises a plethora of cell types connected by intertwined pathways. Optogenetics enriches the neuroscientific tool set for disentangling these neuronal circuits in a manner which exceeds the spatio-temporal precision of previously existing techniques. Technically, optogenetics can be divided in three types of optical and genetic combinations: (1) it is primarily understood as the manipulation of the activity of genetically modified cells (typically neurons) with light, i.e. optical actuators. (2) A second combination refers to visualizing the activity of genetically modified cells (again typically neurons), i.e. optical sensors. (3) A completely different interpretation of optogenetics refers to the light activated expression of a genetically induced construct. Here, we focus on the first two types of optogenetics, i.e. the optical actuators and sensors in an attempt to give an overview into the topic. We first cover methods to express opsins into neurons and introduce strategies of targeting specific neuronal populations in different animal species. We then summarize combinations of optogenetics with behavioral read out and neuronal imaging. Finally, we give an overview of the current state-of-the-art and an outlook on future perspectives.

A starting kit for training and establishing in vivo electrophysiology, intracranial pharmacology, and optogenetics.

BACKGROUND: In accordance with the three R principles of research, animal usage should be limited as much as possible. Especially for the training of entry-level scientists in surgical techniques underlying opto- and electrophysiology, alternative training tools are required before moving on to live animals. We have developed a cost-effective rat brain model for training a wide range of surgical techniques, including, but not limited to optogenetics, electrophysiology, and intracranial pharmacological treatments. RESULTS: Our brain model creates a realistic training experience in animal surgery. The success of the surgeries (e.g. implantation accuracy) is readily assessable in cross sections of the model brain. Moreover, the model allows practicing electrophysiological recordings as well as testing for movement or light related artefacts. COMPARISON WITH EXISTING METHOD(S): The surgery and recording experience in our model closely resembles that in an actual rat in terms of the necessary techniques, considerations and time span. A few differences to an actual rat brain slightly reduce the difficulty in our model compared to a live animal. Thus, entry level scientists can first learn basic techniques in our model before moving on to the slightly more complex procedures in live animals. CONCLUSIONS: Our brain model is a useful training tool to equip scientist who are new in the field of electrophysiology and optogenetic manipulations with a basic skill set before applying it in live animals. It can be adapted to fit the desired training content or even to serve in testing and optimizing new lab equipment for more senior scientists.

Real-time detection of neural oscillation bursts allows behaviourally relevant neurofeedback.

Neural oscillations as important information carrier in the brain, are increasingly interpreted as transient bursts rather than as sustained oscillations. Short (<150 ms) bursts of beta-waves (15-30 Hz) have been documented in humans, monkeys and mice. These events were correlated with memory, movement and perception, and were even suggested as the primary ingredient of all beta-band activity. However, a method to measure these short-lived events in real-time and to investigate their impact on behaviour is missing. Here we present a real-time data analysis system, capable to detect short narrowband bursts, and demonstrate its usefulness to increase the beta-band burst-rate in rats. This neurofeedback training induced changes in overall oscillatory power, and bursts could be decoded from the movement of the rats, thus enabling future investigation of the role of oscillatory bursts.

Publisher Correction: Development of an optogenetic toolkit for neural circuit dissection in squirrel monkeys.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

GluA4-Targeted AAV Vectors Deliver Genes Selectively to Interneurons while Relying on the AAV Receptor for Entry.

Selective gene delivery into subtypes of interneurons remains an important challenge in vector development. Adeno-associated virus (AAV) vector particles are especially promising for intracerebral injections. For cell entry, AAV2 particles are supposed to attach to heparan-sulfate proteoglycans (HSPGs) followed by endocytosis via the AAV receptor (AAVR). Here, we assessed engineered AAV particles deficient in HSPG attachment but competent in recognizing the glutamate receptor 4 (GluA4, also known as GluRD or GRIA4) through a displayed GluA4-specific DARPin (designed ankyrin repeat protein). When injected into the mouse brain, histological evaluation revealed that in various regions, more than 90% of the transduced cells were interneurons, mainly of the parvalbumin-positive subtype. Although part of the selectivity was mediated by the DARPin, the chosen spleen focus-forming virus (SFFV) promoter had contributed as well. Further analysis revealed that the DARPin mediated selective attachment to GluA4-positive cells, whereas gene delivery required expression of AAVR. Our data suggest that cell selectivity of AAV particles can be modified rationally and efficiently through DARPins, but expression of the AAV entry receptor remains essential.

Optogenetic approaches to study the mammalian brain.

Optogenetics has revolutionized neurobiological research by allowing to disentangle intricate neuronal circuits at a spatio-temporal precision unmatched by other techniques. Here, we review current advances of optogenetic applications in mammals, especially focusing on freely moving animals. State-of-the-art strategies allow the targeted expression of opsins in neuronal subpopulations, defined either by genetic cell type or neuronal projection pattern. Optogenetic manipulations of these subpopulations become particularly powerful when combined with behavioral paradigms and neurophysiological readout techniques. Thereby, specific roles can be assigned to identified cells. All-optical approaches with the opportunity to write complex three dimensional patterns into neuronal networks have recently emerged. While clinical implications of the new tool set seem tempting, we emphasize here the role of optogenetics for basic research.

Author Correction: U-Net: deep learning for cell counting, detection, and morphometry.

In the version of this paper originally published, one of the affiliations for Dominic Mai was incorrect: "Center for Biological Systems Analysis (ZBSA), Albert-Ludwigs-University, Freiburg, Germany" should have been "Life Imaging Center, Center for Biological Systems Analysis, Albert-Ludwigs-University, Freiburg, Germany." This change required some renumbering of subsequent author affiliations. These corrections have been made in the PDF and HTML versions of the article, as well as in any cover sheets for associated Supplementary Information.

U-Net: deep learning for cell counting, detection, and morphometry.

U-Net is a generic deep-learning solution for frequently occurring quantification tasks such as cell detection and shape measurements in biomedical image data. We present an ImageJ plugin that enables non-machine-learning experts to analyze their data with U-Net on either a local computer or a remote server/cloud service. The plugin comes with pretrained models for single-cell segmentation and allows for U-Net to be adapted to new tasks on the basis of a few annotated samples.